شناسایی خطواره های گسلی و پهنه بندی خطر زمین لرزه با استفاده از سنجش از دور و سیستم اطلاعات جغرافیایی (مطالعه موردی: شهرستان رومشکان، استان لرستان) (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
زمین لرزه، یکی از مخاطرات طبیعی، همواره در طول تاریخ باعث خرابی ها و از بین رفتن جان انسان های زیادی شده است. برنامه ریزی مناسب برای پیشگیری یا کاهش آثار مخرب خطر زمین لرزه اهمیت ویژه ای دارد؛ بنابراین در راستای پیشگیری و کاهش خطر پذیری این پدیده، اقدام به شناسایی گسل ها و پهنه بندی خطر زمین لرزه در سطح شهرستان رومشکان واقع در استان لرستان شده است. بدین منظور ابتدا با استفاده از تصاویر ماهواره ای سال 2013 لندست 8 سنجنده OLI (ردیف 37 و گذر 166) و اعمال فیلترهای Directional در نرم افزار ENVI و Lineament Extraction ژئومتیکا، خطواره های منطقه شناسایی شده است. سپس با مقایسه خطواره ها با ترکیبات باندی ساخته شده، مدل رقومی ارتفاع (DEM) و نقشه زمین شناسی محدوده موردمطالعه، گسل ها جدا و نقشه آنها در محیط نرم افزار سیستم اطلاعات جغرافیایی (ArcGIS) تهیه شده است. در این پژوهش با استفاده از قضاوت کارشناسی و روش سلسله مراتبی- فازی عوامل مؤثر بر خطر زمین لرزه های شهرستان رومشکان شامل فاصله از گسل، شیب، ژئومورفولوژی، لیتولوژی و فاصله از کانون زمین لرزه های گذشته وزن دهی و نقشه خطر زمین لرزه های منطقه تهیه شده است. براساس نتایج به دست آمده به ترتیب 8/31، 3/34، 3/10، 6/14 و 0/9 درصد از مساحت منطقه در کلاس های خطر خیلی کم، کم، متوسط، زیاد و خیلی زیاد قرار گرفته است. بررسی نقشه حساسیت خطر پدیده زمین لرزه نشان دهنده آن است که بیشترین حساسیت نسبت به خطر زمین لرزه در قسمت های شرقی شهرستان واقع شده است و بخش های مرکزی خطر خیلی کم و کم دارد که استقرار جمعیت در این مناطق پیشنهاد می شود.Identification of Fault Lineaments and Earthquake Hazard Zoning Using Remote Sensing and GIS: A Case Study of Rumeshkan County, Lorestan Province
As a natural hazard, earthquake has always caused destruction and loss of human life throughout history. Proper planning to prevent or reduce the destructive impact of earthquake hazard is of particular importance. In this study, to prevent and decrease the risk of this phenomenon, faults were detected and earthquake risk zoning was done in Rumeshkan County in Lorestan Province. For this purpose, first, the lineaments in the region were detected by using 2013 satellite images from Landsat 8 OLI sensors (row 37 and pass 166) and applying Directional Filters in ENVI software, as well as Lineament Extraction in Geomatica software. Afterwards, by comparing the lines with the constructed band combinations, the Digital Elevation Model (DEM) and geological map of the study area were investigated, the faults were separated, and their map was prepared in the Geographic Information System (ArcGIS). In this study, by using expert judgment method and AHP-Fuzzy, the factors that affected the risk of earthquakes in Rumeshkan County, including distance from fault, slope, geomorphology, lithology, and distance from epicenters of past earthquakes were weighted and the seismic hazard map of the region was prepared. According to the obtained results, 31.8, 34.3, 10.3, 14.6, and 9.0% of the area were in very low, low, medium, high, and very high hazard classes, respectively. Examination of the earthquake hazard sensitivity map showed that the highest sensitivity to seismic hazard was in the eastern parts of the county and that the central parts had very low and low risks; thus, settlement of population in the latter areas is recommended. Keywords : earthquake, Rumeshkan, remote asensing, GIS, AHP-fuzzy Introduction Earthquakes have always been among the most important natural hazards. Every year, a large number of people in the world are affected by the adverse effects of earthquake. To decrease human and economic losses, as well as their social consequences, it is necessary to gain an accurate knowledge of the risks of earthquakes in different places based on the current knowledge and the latest reliable technologies. Risk zoning is an important approach in the pre-crisis management process that greatly assists planners and managers to take measures to reduce earthquakes earthquake vulnerability. The main issues are the selection of vulnerability criteria and the way of combining them, as well as selecting an appropriate model that can best represent the rate of vulnerability. Today, with the increasing science advancement, satellites and satellite imagery have progressed; therefore, the use of remote sensing methods and satellite image processing appear to be highly efficient for identifying and studying geological phenomena, such as faults and lineaments. GIS is also one of the most powerful software in the field of environmental hazard mapping that contributes to efficient management of spatial and temporal data. Methodology Manual, automatic, and semi-automatic methods are used to extract tha data of lineaments and faults. In this study, a semi-automatic method was used, which is a combination of automatic and manual methods and is more reliable with a good speed. For this purpose, the 2013 Landsat 8 images taken by OLI sensor (row 37 and pass 166) were analyzed. In this study, first the lineaments in this area were extracted by applying Lineament Extraction Filter in Geomatica software. Then, by spatial highlighting and applying directional filters on 8-band images obtained from the Landsat 8 satellite image of OLI sensor, as well as creating band combinations, the faults in the area were manually identified. AHP-fuzzy was used for earthquake hazard zoning in Rumeshkan County. In addition to the fault map of the region, other factors, including slope, geomorphology, lithology, and distance from the epicenters of past earthquakes, were used. The fuzzy hierarchical integrated model has a high efficiency in earthquake risk zoning due to removing the inherent inaccuracy and uncertainty of decision makers' perceptions and reflecting their opinions as a definitive number. After weighting the factors, by combining the maps in the environment of Geographic Information System (GIS) software, the earthquake zoning map of the region was prepared. Discussion In this research, after examining the factors affecting the earthquake risk, a map of each of the factors was prepared in the environment of ArcGIS software. The results obtained from the analysis of each factor were as follows: The study of lithology and geomorphology of the region showed that due to the looseness of Quaternary alluvial sediments, this unit had the highest sensitivity to earthquake hazard and the highest weight was assigned to it. Investigation of the area slope according to the expert judgments indicated that the highest sensitivity to earthquake hazard was related to the highest slope degrees, which could be attributed to the low shear strength of materials at high slopes. The results obtained from the study of the faults in the region revealed that sensitivity to earthquakes increased by decreasing distance from the faults because earthquakes themselves were caused by the movement of faults. Also, the sensitivity increased as the distances from the epicenters of past earthquakes decreased. After examining the factors affecting earthquake risk, the map of each factor was fuzzified by using the fuzzy membership functions. For this purpose, to standardize the maps, the slope and lithology maps were respectively obtained through incremental linear and Gaussian membership functions to determine distances from the faults, epicenters of old earthquakes, and geomorphology of the faults. Considering the fact that each layer had a different impact on seismic hazard zoning, weighting of the layers and substrates was necessary. In the hierarchical analysis process, first, a pairwise comparison was done and the results were transferred to the Expert Choice software in order to calculate the weight of each factor. Based on the obtained findings, the fault layer had the most important role in preparing the seismic zoning map of the study area. According to the prepared lineament maps, the faults were mostly concentrated in the eastern parts of Rumeshkan County. Conclusion Most studies concerning fracture and fault modeling in each region depend on analysis of lineaments. In this research, a remote sensing technique (OLI sensor satellite imagery) was used to obtain an integrated digital map of the region's lineaments. The results showed that the use of a semi-automatic method was one of the fastest and most accurate approaches for extracting the maps of faults and fractures. In this study, 5 factors were selected as effective factors in the seismic hazard zoning of Rumeshkan City. Prioritization of the factors by using the hierarchical analysis showed that the factors of distance from fault, distances from epicenters of past earthquakes, lithology, slope, and geomorphology played the most important roles in preparing the seismic hazard map, respectively. According to the results of seismic hazard zoning, >23% of the area was in the high- and very high-risk classes, covering most of the eastern part of the study area. Combination of the residential area map with the earthquake risk zoning map also showed that the residential areas located in the eastern, western, and central parts were in high- and very high-risk classes, low- to medium-risk class, and very low- and low-risk classes, respectively. Chaqabol, the capital of the county, was located at the central part. References - Bimal, N., Yadav, O. P., & Murat, A. (2010). A fuzzy- AHP approach to prioritization of CIS attributes in target planning for automotive product development. Expert System with Application Journal , 37, pp. 6775- 6786. - Fayaz, M., Romshoo, S. A., Rashid, I., & Chandra, R. (2022). Earthquake Vulnerability Assessment of the Built Environment in Srinagar City, Kashmir, Himalaya, Using GIS. Natural Hazards and Earth System Sciences , pp. 1-35. https://doi.org/10.5194/nhess-2022-155 - Gannouni, S. and Gabtni, H. (2015). 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